Estimated glomerular filtration rate in Brazilian adults with sickle cell disease: results from the REDS-III multicenter cohort study.

Chronic kidney disease (CKD) has a significant impact on sickle cell disease (SCD) morbidity and mortality. Early identification of individuals at highest risk of developing CKD may allow therapeutic intervention to prevent worse outcomes. This study aimed to evaluate the prevalence and risk factors for reduced estimated glomerular filtration rate (eGFR) among adults with SCD in Brazil. Participants in the REDS-III multicenter SCD cohort with more severe genotypes aged ≥ 18 years with at least two serum creatinine values were analyzed. The eGFR was calculated using the Jamaica Sickle Cell Cohort Study GFR equation. The eGFR categories were defined according to the K/DOQI. Participants with eGFR ≥ 90 were compared to those with those with eGFR < 90. Among the 870 participants, 647 (74.4%) had eGFR ≥ 90, 211 (24.3%) had eGFR 60 to 89, six (0.7%) had eGFR 30 to 59, and six (0.7%) had ESRD. Male sex (OR: 37.3; 95%CI: 22.4-65.1), higher age (OR: 1.04; 95%CI: 1.02-1.06), higher diastolic blood pressure (OR: 1.03; 95%CI: 1.009-1.06), lower Hb (OR: 0.80; 95%CI: 0.68-0.93), and lower reticulocytes (OR: 0.94; 95%CI: 0.89-0.99) levels were independently associated with eGFR < 90. There was a trend towards higher odds of death in participants with eGFR < 90 (OR: 1.8; 95%CI: 0.95-3.32; p = 0.065). In turn, participants with eGFR < 60 had a 12.2 (95%CI: 2.1-96.9) times higher odds for death when compared to those with eGFR ≥ 60. In this study, eGFR < 90 was observed in one-quarter of adults. Older age, male sex, higher diastolic blood pressure, lower hemoglobin, and lower reticulocyte levels were associated with occurrence of eGFR < 90. Estimated GFR < 60 increased the risk of mortality.

Hb S/ß-Thalassemia in the REDS-III Brazil Sickle Cell Disease Cohort: Clinical, Laboratory and Molecular Characteristics.

We described the clinical, laboratory and molecular characteristics of individuals with Hb S (HBB: c.20A>T)/ß-thalassemia (Hb S/ß-thal) participating in the Recipient Epidemiology and Donor Evaluation Study (REDS-III) Brazil Sickle Cell Disease cohort. HBB gene sequencing was performed to genotype each ß-thal mutation. Patients were classified as Hb S/ß0-thal, Hb S/ß+-thal-severe or Hb S/ß+-thal based on prior literature and databases of hemoglobin (Hb) variants. Characteristics of patients with each ß-thal mutation were described and the clinical profile of patients grouped into Hb S/ß0-thal, Hb S/ß+-thal and Hb S/ß+-thal-severe were compared. Of the 2793 patients enrolled, 84 (3.0%) had Hb S/ß0-thal and 83 (3.0%) had Hb S/ß+-thal; 40/83 (48.2%) patients with Hb S/ß+-thal had mutations defined as severe. We identified 19 different ß-thal mutations, eight Hb S/ß0-thal, three Hb S/ß+-thal-severe and eight Hb S/ß+-thal. The most frequent ß0 and ß+ mutations were codon 39 (HBB: c.118C>T) and IVS-I-6 (T>C) (HBB: c.92+6T>C), respectively. Individuals with Hb S/ß0-thal had a similar clinical and laboratory phenotype when compared to those with Hb S/ß+-thal-severe. Individuals with Hb S/ß+-thal-severe had significantly lower total Hb and Hb A levels and higher Hb S, white blood cell (WBC) count, platelets and hemolysis markers when compared to those with Hb S/ß+-thal. Likewise, individuals with Hb S/ß+-thal-severe showed a significantly higher occurrence of hospitalizations, vaso-occlusive events (VOE), acute chest syndrome (ACS), splenic sequestration, blood utilization, and hydroxyurea (HU) therapy.

Social and behavioral characteristics of male blood donors and their sexual partners: an analysis to define risk subsets.

BACKGROUND: Men who have sex with men in Brazil are deferred from donation for 1 year since their last sexual contact. Legal proceedings in front of the Brazilian Supreme Court could compel blood collection agencies to discontinue use of sexual orientation questions. METHODS: Data from male participants in a completed HIV risk factor case-control study were used to evaluate whether it is possible to differentiate donors at lower and higher risk for HIV using two analytical approaches: latent class and random forest analyses. RESULTS: Male blood donors were divided into three distinct risk profile classes. Class 1 includes donors who are heterosexual (96.4%), are HIV negative (88.7%), have a main partner (99.4%), and practice unprotected sex (77.8%). Class 2 includes donors who are men who have sex with men /bisexuals' (100.0%), are HIV positive (97.4%), and were not aware of their sexual partners' HIV status (80.3%). Class 3 includes donors who are heterosexual (84.1%), practice unprotected vaginal/anal heterosexual sex (66.8% vs. 40.9%), and were both HIV positive and HIV negative (49.5% vs. 50.5%). We also found that asking donors about their partner(s)' HIV serostatus could replace asking about donors' sexual orientation and types of partners with relatively minor shifts in sensitivity (0.76 vs. 0.58), specificity (0.89 vs. 0.94), and positive predictive value (0.85 vs. 0.88). CONCLUSION: Sexual orientation questions on the donor questionnaire could be replaced without great loss in the sensitivity, specificity, and positive predictive value. Social and sexual behaviors of donors and their partners are proxies for HIV risk and can help to develop modified questions that will need controlled trials to be validated.

Data-intensive analysis of HIV mutations.

BACKGROUND: In this study, clustering was performed using a bitmap representation of HIV reverse transcriptase and protease sequences, to produce an unsupervised classification of HIV sequences. The classification will aid our understanding of the interactions between mutations and drug resistance. 10,229 HIV genomic sequences from the protease and reverse transcriptase regions of the pol gene and antiretroviral resistant related mutations represented in an 82-dimensional binary vector space were analyzed. RESULTS: A new cluster representation was proposed using an image inspired by microarray data, such that the rows in the image represented the protein sequences from the genotype data and the columns represented presence or absence of mutations in each protein position.The visualization of the clusters showed that some mutations frequently occur together and are probably related to an epistatic phenomenon. CONCLUSION: We described a methodology based on the application of a pattern recognition algorithm using binary data to suggest clusters of mutations that can easily be discriminated by cluster viewing schemes.

Thinking out of the box: revisiting health surveillance based on medical records.

Despite the considerable advances in the last years, the health information systems for health surveillance still need to overcome some critical issues so that epidemic detection can be performed in real time. For instance, despite the efforts of the Brazilian Ministry of Health (MoH) to make COVID-19 data available during the pandemic, delays due to data entry and data availability posed an additional threat to disease monitoring. Here, we propose a complementary approach by using electronic medical records (EMRs) data collected in real time to generate a system to enable insights from the local health surveillance system personnel. As a proof of concept, we assessed data from São Caetano do Sul City (SCS), São Paulo, Brazil. We used the "fever" term as a sentinel event. Regular expression techniques were applied to detect febrile diseases. Other specific terms such as "malaria," "dengue," "Zika," or any infectious disease were included in the dictionary and mapped to "fever." Additionally, after "tokenizing," we assessed the frequencies of most mentioned terms when fever was also mentioned in the patient complaint. The findings allowed us to detect the overlapping outbreaks of both COVID-19 Omicron BA.1 subvariant and Influenza A virus, which were confirmed by our team by analyzing data from private laboratories and another COVID-19 public monitoring system. Timely information generated from EMRs will be a very important tool to the decision-making process as well as research in epidemiology. Quality and security on the data produced is of paramount importance to allow the use by health surveillance systems.

Risk factors for long coronavirus disease 2019 (long COVID) among healthcare personnel, Brazil, 2020-2022.

OBJECTIVE: To determine risk factors for the development of long coronavirus disease 2019 (COVID-19) in healthcare personnel (HCP). METHODS: We conducted a case-control study among HCP who had confirmed symptomatic COVID-19 working in a Brazilian healthcare system between March 1, 2020, and July 15, 2022. Cases were defined as those having long COVID according to the Centers for Disease Control and Prevention definition. Controls were defined as HCP who had documented COVID-19 but did not develop long COVID. Multiple logistic regression was used to assess the association between exposure variables and long COVID during 180 days of follow-up. RESULTS: Of 7,051 HCP diagnosed with COVID-19, 1,933 (27.4%) who developed long COVID were compared to 5,118 (72.6%) who did not. The majority of those with long COVID (51.8%) had 3 or more symptoms. Factors associated with the development of long COVID were female sex (OR, 1.21; 95% CI, 1.05-1.39), age (OR, 1.01; 95% CI, 1.00-1.02), and 2 or more SARS-CoV-2 infections (OR, 1.27; 95% CI, 1.07-1.50). Those infected with the SARS-CoV-2 δ (delta) variant (OR, 0.30; 95% CI, 0.17-0.50) or the SARS-CoV-2 o (omicron) variant (OR, 0.49; 95% CI, 0.30-0.78), and those receiving 4 COVID-19 vaccine doses prior to infection (OR, 0.05; 95% CI, 0.01-0.19) were significantly less likely to develop long COVID. CONCLUSIONS: Long COVID can be prevalent among HCP. Acquiring >1 SARS-CoV-2 infection was a major risk factor for long COVID, while maintenance of immunity via vaccination was highly protective.

Is Severity Score Associated With Indication for Hematopoietic Stem Cell Transplantation in Individuals With Sickle Cell Anemia?

Manifestations of sickle cell disease (SCD) begin early in childhood and cause morbidity and decreased life expectancy. Hematopoietic stem cell transplantation (HSCT) is curative but associated with risk of mortality attributable to the transplant. This risk should be counterbalanced with SCD morbidity and mortality. A severity score using a Bayesian network model was previously validated to predict the risk of death in adult individuals with SCD. The objective of this study is to calculate the severity scores of participants in a multicenter cohort of Brazilians with SCD, using a previously published Bayesian network-derived score, associated with risk of death and then compare the severity scores between participants with and without an indication for HSCT as defined by the Brazilian Ministry of Health (MoH) criteria. This is an observational, retrospective study. We analyzed 2063 individuals with sickle cell anemia from the Recipient Epidemiology and Donor Evaluation Study-III Brazil SCD cohort and applied a Bayesian network-derived score to compare candidates and non-candidates for HSCT according to the Brazilian MoH transplant criteria. Classical statistical methods were used to analyze data and make comparisons. We compared severity scores between cohort members with (n = 431) and without (n = 1632) HSCT indications according to Brazilian MoH. Scores were not different in adult participants with ≥1 HSCT indication when compared to those with no indication (mean 0.342 versus 0.292; median 0.194 versus 0.183, P = .354) and receiver operating characteristic curves did not demonstrate an obvious threshold to differentiate participants with or without HSCT indications. Severity score may predict risk of death but does not differentiate HSCT candidates. Current indications should be evaluated to ensure that patients with more severe disease who might benefit from HSCT are appropriately identified.